Supporting Information for: What Have We Learned About Gender From Candidate Choice Experiments? A Meta-analysis of 67 Factorial Survey Experiments

Susanne Schwarz and Alexander Coppock∗

June 30, 2020

Contents

A Study-by-study CATEs by other candidate attributes 2

B Digital measurement of coefficient estimates 34

∗Susanne Schwarz is a Doctoral Candidate in the Department of Politics, Princeton University. Alexander Coppock is Assistant Professor of Political Science, Yale University.

1 A Study-by-study CATEs by other candidate attributes

In this appendix, we show the effects of gender, conditional on other candidate characteristics for a subset of studies. Since most studies included in our analysis were not primarily concerned with the effects of candidate gender on vote choice, they included a wide range of other candidate characteristics. Table A.1 provides an overview of the attributes included in this analysis. Figure A.1 shows the distribution of CATEs, conditional on each of the attributes listed in Table A.1. The figure tells a very consistent story. Not only do the average treatment effects of gender on vote choice tend to be positive, so too do the conditional average treatment effects of gender. Our main takeaway from Figure A.1 is that the effect of candidate gender on vote choice does vary somewhat depending on the level of the other candidate characteristics but is typically positive. In the remainder of the appendix, we show the study-by-study estimates that make up Figure A.1.

2 Table A.1: Overview of Attributes (Other Than Gender) Included in Study Designs

Study Design Attributes Aguilar, Cunow, and Desposato (2015), Sao Paulo Race, ballot length Bansak, Hainmueller, Hopkins, and Yamamoto (2018), USA - MTurk State of Residence, Age, Race/Ethnicity, Annual Income, Marital status, Religion, College Education, Military Service, Political Party , Political experience, Largest campaign contributor, Position on Health Care, Position on Abortion, Position on Gay Marriage, Favorite Music, Favorite sport, Car Bansak, Hainmueller, Hopkins, and Yamamoto (2018), USA - SSI State of Residence, Age, Race/Ethnicity, Annual Income, Marital status, Religion, College Education, Military Service, Political Party , Political experience, Largest campaign contributor, Position on Health Care, Position on Abortion, Position on Gay Marriage, Favorite Music, Favorite sport, Car Campbell, Cowley, Vivyan, and Wagner (2016), UK - Frequency of MP Dissent Constituency Effort, Frequency of Dissent, Political Party, Tenure of Elected Office Campbell, Cowley, Vivyan, and Wagner (2016), UK - Type of MP Dissent Constituency Effort, Type of Dissent, Political Party, Views important for policy Carnes and Lupu (2016), Argentina Occupation , Education , Ideology , Experience Carnes and Lupu (2016), UK Occupation, Education, Party Carnes and Lupu (2016), USA Occupation, Office, Education, Race Clayton, Robinson, Johnson, Muriaas (2019), Malawi Education, leadership experience, family structure, occupation, policy priority, matrilineal vs. patrilineal kinship Eggers, Vivyan, and Wagner (2018), UK Party ID, age, profession, corruption history Hainmueller, Hopkins, and Yamamoto (2014), USA Age, race or ethnicity, education, income, profession, religion, military service Henderson et al. (2019), USA Personality, Endorsements, Issue Position 1, Issue Position 2, Political Record, Religion, Race, Profession Holman, Merolla, and Zechmeister (2016), USA Context, Opponent Hopkins, Daniel (2014), USA Race/ethnicity, party ID, religion, issue positions on health care, gun control, abortion, government spending and gay marriage, annual income Kirkland and Coppock (2017), USA - MTurk Age, Experience, Occupation, Race, Party Kirkland and Coppock (2017), USA - YouGov Age, Experience, Occupation, Race, Party Mo (2015), Florida Competition Saha and Weeks (2019), DLABSS 1 Progressive, Political Agenda, Political Experience Saha and Weeks (2019), USA, DLABSS 2 Profession, Age, Progressive, Political Agenda, Political Experience Saha and Weeks (2019), USA, SSI Personality traits, Family, Progressive, Political Agenda Saha and Weeks (2019), UK, Prolific Personality traits, Family, Progressive, Political Agenda Sen (2017), USA, SSI 1 Political Party, Religion, Education, Court experience, Race/Ethnicity, Age, Profession Sen (2017), USA, SSI 2 Religion, Education, Court experience, Race/Ethnicity, Age, Profession Teele, Kalla, and Rosenbluth (2018), USA Occupation, Experience, Age, Children, Spouse’s Job Visconti (2017), Chile Ideology, age, profession, political experience, position on flood relief Mares and Visconti (2020), Romania Experience, Negative Inducement, Positive Inducement, Investigation, Policy/Public Goods, Income Harris, Kao, and Lust (2020), Malawi Election Type, Ethnicity, Living Status, Partisanship, Type of future promise, Endorser Endowment, Actions at campaign rallies, Target of distribution Harris, Kao, and Lust (2020), Zambia Election Type, Ethnicity, Living Status, Partisanship, Type of future promise, Endorser Endowment, Actions at campaign rallies, Target of distribution Horne (2020), UK Party, Occupation, Education, Ideology Bischof and Senninger (2020), Germany Knowledge, Eurozone reform, Absent days, Motivation, Experience, Party Shaffner and Green (2020), YouGov Blue Age, Environment, Health, Strategy, Background Costa (2020), USA - Lucid Constituent Relations, Latest Tweet, Party Leeper and Robison (2020), US, SSI Race, Religion, Occupation, Party, Military Service, Education, Trans-Pacific Partnership, ISIS, Cap and trade, Tax the rich, Path to citizenship Clayton and Nyhan (2020), USA - Donors Partisanship, Race, Voting, Investigations, Compromise, Courts, Discrimination, Taxes Clayton and Nyhan (2020), USA - YouGov Partisanship, Race, Voting, Investigations, Compromise, Courts, Discrimination, Taxes Blackman and Jackson (2019), Tunisia - Face-to-Face Party, Job, Town, Education, Age, Policy, Experience Blackman and Jackson (2019), Tunisia - YouGov Party, Job, Town, Education, Age, Policy, Experience Ono and Yamada (2018), Japan Education, Specialization, Social Issues, Economic Issues, Military Issues Arnesen, Duell, and Johannesson (2019), Norway 1 Age, Education, Region, Relationship, Religion, Work Arnesen, Duell, and Johannesson (2019), Norway 2 Age, Education, Region, Relationship, Religion, Work Martin and Blinder (2020), UK, YouGov Ethnicity, Entry into politics, Immigration policy, Law enforcement, Party Goyal (2020), India Party, Caste, Occupation, Background, Policy Lemi (2020), USA, Qualtrics Experience, Ideology, Nativity, Party

3 Figure A.1: 954 Estimates of the Effect of Candidate Gender, Conditional on Auxilliary Candidate Attributes

−20 −10 0 10 20 CATE estimate in percentage points

4 Figure A.2: Aguilar, Cunow, and Desposato (2015), Sao Paulo

10.3 (4.8) Candidate Race: white

1.9 (4.8) Candidate Race: black

−20 −10 0 10 20 CATE estimate in percentage points

Figure A.3: Arnesen, Duell, and Johannesson (2019), Norway

Work: Self−employed 5.5 (3.7) Work: Oil worker 1.5 (3.6) Work: No work experience 7.4 (3.5) Work: IT−consultant 8.4 (3.6) Work: Farmer 10.8 (3.6) Work: Care worker −5.3 (3.9) Religion: No religion 3.4 (2.5) Religion: Islam 5.6 (2.6) Religion: Christianity 5.9 (2.7) Relationship: Married 3.7 (2.6) Relationship: Living alone 5.3 (2.7) Relationship: Cohabitant 6.0 (2.5) Region: Western Norway 7.6 (3.7) Region: Southern Norway 0.2 (3.6) Region: Oslo 6.7 (3.7) Region: Northern Norway 5.9 (3.6) Region: Eastern Norway 0.8 (3.6) Region: Central Norway 9.6 (3.6) Education: University 1.3 (3.0) Education: Ph.D. 9.4 (2.9) Education: High school 6.3 (3.0) Education: Elementary school 3.0 (3.0) Age: 80 years 6.3 (4.0) Age: 70 years 1.0 (3.8) Age: 60 years 5.7 (4.0) Age: 50 years 1.6 (4.0) Age: 40 years 8.0 (4.0) Age: 30 years 7.9 (3.8) Age: 22 years 3.8 (3.9) −20 −10 0 10 20 CATE estimate in percentage points

5 Figure A.4: Arnesen, Duell, and Johannesson (2019), Norway

Work: Self−employed 3.3 (3.1) Work: Oil worker 14.1 (3.0) Work: No work experience 4.6 (3.3) Work: IT−consultant −0.5 (3.0) Work: Farmer 7.7 (3.0) Work: Care worker 7.4 (3.0) Religion: No religion 4.3 (2.2) Religion: Islam 3.1 (2.1) Religion: Christianity 11.0 (2.2) Relationship: Married 5.4 (2.2) Relationship: Living alone 6.3 (2.1) Relationship: Cohabitant 6.6 (2.2) Region: Western Norway 4.4 (3.1) Region: Southern Norway 10.7 (3.1) Region: Oslo 10.2 (3.1) Region: Northern Norway 3.7 (3.2) Region: Eastern Norway 3.7 (2.9) Region: Central Norway 4.3 (3.0) Education: University 4.3 (2.6) Education: Ph.D. 5.3 (2.6) Education: High school 8.4 (2.5) Education: Elementary school 6.5 (2.5) Age: 80 years 1.6 (3.3) Age: 70 years 2.8 (3.3) Age: 60 years 3.1 (3.4) Age: 50 years 4.4 (3.3) Age: 40 years 10.2 (3.4) Age: 30 years 10.9 (3.3) Age: 22 years 10.2 (3.4) −20 −10 0 10 20 CATE estimate in percentage points

6 Figure A.5: Bansak, Hainmueller, Hopkins, and Yamamoto (2018), USA - MTurk

State of Residence: Ohio 1.6 (0.6) State of Residence: NA 0.5 (0.5) State of Residence: Massachusetts −0.1 (0.7) State of Residence: Colorado −0.2 (0.6) State of Residence: Alabama 0.4 (0.7) Religion: None 0.2 (0.6) Religion: NA 1.2 (0.5) Religion: Mainline Protestant 0.0 (0.7) Religion: Evangelical Protestant −0.9 (0.7) Religion: Catholic 0.9 (0.6) Race/Ethnicity: White −0.2 (0.7) Race/Ethnicity: Nonwhite 0.6 (0.4) Race/Ethnicity: NA 0.5 (0.5) Position on Health Care: NA 0.7 (0.5) Position on Health Care: government should do more 1.0 (0.5) Position on Health Care: government should do less −0.3 (0.5) Position on Gay Marriage: opposes gay marriage 0.9 (0.5) Position on Gay Marriage: NA 0.7 (0.5) Position on Gay Marriage: favors gay marriage −0.3 (0.5) Position on Abortion: pro−life 0.4 (0.6) Position on Abortion: pro−choice 0.1 (0.6) Position on Abortion: neutral 1.0 (0.6) Position on Abortion: NA 0.4 (0.5) Political Party: Republican 0.5 (0.4) Political Party: Democrat 0.5 (0.4) Political experience: U.S. senator 0.9 (0.7) Political experience: state attorney general 0.6 (0.7) Political experience: none 0.6 (0.7) Political experience: NA 0.2 (0.5) Political experience: governor 0.3 (0.6) Military Service: served in U.S. military 0.6 (0.5) Military Service: no military service 0.6 (0.5) Military Service: NA 0.2 (0.5) Marital status: single 0.2 (0.6) Marital status: NA 0.4 (0.5) Marital status: married 1.2 (0.6) Marital status: divorced 0.1 (0.6) Largest campaign contributor: wall street firms −0.5 (0.6) Largest campaign contributor: teachers' unions 0.6 (0.7) Largest campaign contributor: oil companies 0.1 (0.6) Largest campaign contributor: NA 0.9 (0.5) Largest campaign contributor: auto workers' unions 0.6 (0.7) Favorite sport: soccer 0.3 (0.7) Favorite sport: NA 0.9 (0.5) Favorite sport: football 0.6 (0.7) Favorite sport: basketball −0.5 (0.7) Favorite sport: baseball 0.4 (0.7) Favorite Music: rock −0.1 (0.7) Favorite Music: NA 0.6 (0.5) Favorite Music: hip hop 0.0 (0.7) Favorite Music: country 1.4 (0.7) Favorite Music: classical 0.2 (0.6) College Education: Less than College 0.5 (0.4) College Education: College 0.4 (0.4) Car: Toyota Sedan 1.4 (0.6) Car: Toyota pick−up truck 1.1 (0.6) Car: NA 0.1 (0.5) Car: Ford Sedan 0.5 (0.6) Car: Ford pick−up truck −0.4 (0.7) Annual Income: NA 1.2 (0.5) Annual Income: $75k −0.9 (0.7) Annual Income: $5.1m 0.1 (0.6) Annual Income: $32k 1.1 (0.7) Annual Income: $180k −0.1 (0.7) Age: NA 0.5 (0.5) Age: 72 0.0 (0.7) Age: 63 0.7 (0.7) Age: 54 0.4 (0.8) Age: 45 0.8 (0.7) Age: 36 0.4 (0.7) −20 −10 0 10 20 CATE estimate in percentage points

7 Figure A.6: Bansak, Hainmueller, Hopkins, and Yamamoto (2018), USA - SSI

State of Residence: Ohio −0.8 (1.4) State of Residence: NA 0.3 (0.9) State of Residence: Massachusetts 0.5 (1.3) State of Residence: Colorado 0.4 (1.3) State of Residence: Alabama 0.6 (1.4) Religion: None −1.1 (1.4) Religion: NA 1.0 (0.8) Religion: Mainline Protestant 1.0 (1.3) Religion: Evangelical Protestant −0.7 (1.5) Religion: Catholic −1.1 (1.4) Race/Ethnicity: White −0.3 (1.3) Race/Ethnicity: Nonwhite −0.1 (0.8) Race/Ethnicity: NA 0.8 (0.9) Position on Health Care: NA 0.3 (0.9) Position on Health Care: government should do more −0.6 (0.9) Position on Health Care: government should do less 0.9 (1.0) Position on Gay Marriage: opposes gay marriage 0.3 (1.0) Position on Gay Marriage: NA −0.2 (0.9) Position on Gay Marriage: favors gay marriage 0.7 (0.9) Position on Abortion: pro−life −0.3 (1.3) Position on Abortion: pro−choice 0.8 (1.3) Position on Abortion: neutral 1.1 (1.2) Position on Abortion: NA −0.2 (0.8) Political Party: Republican −0.5 (0.8) Political Party: Democrat 0.9 (0.7) Political experience: U.S. senator −0.0 (1.3) Political experience: state attorney general 0.5 (1.4) Political experience: none 0.4 (1.3) Political experience: NA 0.2 (0.9) Political experience: governor 0.0 (1.4) Military Service: served in U.S. military −0.4 (1.0) Military Service: no military service 1.0 (1.0) Military Service: NA 0.1 (0.9) Marital status: single 0.7 (1.1) Marital status: NA 1.5 (0.9) Marital status: married −2.0 (1.2) Marital status: divorced −0.6 (1.2) Largest campaign contributor: wall street firms 1.6 (1.4) Largest campaign contributor: teachers' unions 1.5 (1.4) Largest campaign contributor: oil companies −0.6 (1.4) Largest campaign contributor: NA −0.5 (0.9) Largest campaign contributor: auto workers' unions 0.5 (1.3) Favorite sport: soccer −0.7 (1.4) Favorite sport: NA 0.4 (0.9) Favorite sport: football 2.1 (1.4) Favorite sport: basketball −1.1 (1.3) Favorite sport: baseball −0.2 (1.3) Favorite Music: rock −0.5 (1.4) Favorite Music: NA 0.5 (0.9) Favorite Music: hip hop 0.3 (1.3) Favorite Music: country 0.4 (1.3) Favorite Music: classical −0.1 (1.3) College Education: Less than College −0.1 (0.8) College Education: College 0.4 (0.8) Car: Toyota Sedan −1.1 (1.4) Car: Toyota pick−up truck −0.6 (1.3) Car: NA 0.6 (0.9) Car: Ford Sedan 1.6 (1.4) Car: Ford pick−up truck −0.5 (1.5) Annual Income: NA 1.1 (0.9) Annual Income: $75k −1.0 (1.3) Annual Income: $5.1m −0.1 (1.2) Annual Income: $32k −0.1 (1.2) Annual Income: $180k −0.2 (1.4) Age: NA 0.2 (0.9) Age: 72 −0.2 (1.5) Age: 63 −1.0 (1.5) Age: 54 2.0 (1.5) Age: 45 −0.7 (1.5) Age: 36 0.8 (1.5) −20 −10 0 10 20 CATE estimate in percentage points

8 Figure A.7: Bischof and Senninger (2020)

Party: SPD 3.2 (2.3) Party: FDP −0.1 (2.3) Party: Die Linke −2.3 (2.3) Party: CDU/CSU 5.4 (2.3) Party: B90/Grüne 2.4 (2.3) Party: AfD 3.7 (3.8) Motivation: to serve the party 2.0 (1.7) Motivation: to represent ordinary people 1.7 (1.7) Motivation: to impact personally 0.8 (1.8) Knowledge: national politics 2.9 (1.8) Knowledge: European politics −1.0 (1.7) Knowledge: constituency 2.6 (1.7) Experience: two years 2.4 (1.8) Experience: ten years 1.8 (2.0) Experience: six years 0.3 (2.1) Experience: forteen years 1.5 (2.1) Eurozone reform: none 1.3 (1.7) Eurozone reform: much 3.9 (1.7) Eurozone reform: little −0.3 (1.7) Absent days: meetings in the constituency 1.1 (1.8) Absent days: meetings in Berlin 1.2 (1.7) Absent days: meetings at the EU−level 2.2 (1.7) −20 −10 0 10 20 CATE estimate in percentage points

9 Figure A.8: Blackman and Jackson (2019), Tunisia - Face-to-Face

Town: within 40 km of here −4.8 (3.7) Town: within 30 km of here 0.7 (3.7) Town: within 20 km of here −5.7 (3.7) Town: within 10 km of here 1.8 (3.7) Policy: Improve women's rights −4.7 (3.8) Policy: Improve the economic situation −1.1 (3.9) Policy: Improve security −0.4 (3.6) Policy: Fight corruption −1.1 (3.5) Party: UPL 0.2 (6.2) Party: Popular Front 1.6 (5.9) Party: Nidaa Tounes −4.8 (5.6) Party: Machrouu Tounes −3.1 (5.9) Party: Initiative Party 4.0 (5.3) Party: Ennahda −5.6 (5.6) Party: Democratic Current −9.0 (5.9) Party: Current of Love 4.6 (5.9) Party: al−Irada Movement 0.2 (5.6) Party: Afek Tounes −8.2 (6.1) Job: Union Activist −3.5 (4.5) Job: Teacher −4.5 (4.7) Job: Political Activist −10.1 (4.1) Job: Lawyer 4.7 (4.4) Job: Employee in the private sector 1.8 (4.4) Job: Director 0.4 (4.3) Experience: Has previously served in the government 1.5 (2.7) Experience: Has not previously served in the government −5.4 (2.7) Education: Studied outside of Tunisia −5.3 (3.2) Education: Masters −0.6 (3.3) Education: Bachelors −0.7 (3.1) Age: 70 −5.6 (4.3) Age: 60 0.4 (4.1) Age: 50 −6.1 (4.1) Age: 40 7.2 (4.3) Age: 30 −5.5 (3.9) −20 −10 0 10 20 CATE estimate in percentage points

10 Figure A.9: Blackman and Jackson (2019), Tunisia - YouGov

Town: Within 40 km of your municipality −0.7 (2.7) Town: Within 30 km of your municipality −2.7 (2.8) Town: Within 20 km of your municipality −1.9 (2.6) Town: Within 10 km of your municipality 2.1 (2.7) Policy: Improve women's rights −3.4 (2.7) Policy: Improve the economic situation 3.1 (2.7) Policy: Improve security −2.8 (2.6) Policy: Fight corruption 0.5 (2.8) Party: Nidaa Tounes 1.5 (3.0) Party: Jabha Shabiyya −1.1 (3.0) Party: Independent List −3.8 (2.9) Party: Ennahda 2.2 (3.1) Party: Democratic Current −5.5 (3.1) Job: Union Activist 2.5 (3.3) Job: Teacher 0.6 (3.1) Job: Private sector employee −3.3 (3.4) Job: Political Activist 1.5 (3.6) Job: Lawyer −4.4 (3.4) Job: Director of an organization −1.6 (3.3) Experience: Has previously served in the government 2.0 (1.9) Experience: Has not previously served in the government −3.6 (1.9) Education: Studied outside of Tunis −0.9 (2.3) Education: Masters −1.7 (2.3) Education: Bachelors 0.8 (2.4) Age: 71 −2.6 (3.0) Age: 60 1.6 (3.2) Age: 51 −0.8 (3.1) Age: 42 −2.0 (3.0) Age: 33 −1.0 (3.0) −20 −10 0 10 20 CATE estimate in percentage points

11 Figure A.10: Campbell, Cowley, Vivyan, and Wagner (2016), UK - Frequency of MP Dissent

Tenure of Elected Office: 3 2.9 (1.5) Tenure of Elected Office: 21 0.9 (1.5) Tenure of Elected Office: 10 0.5 (1.6) Political Party: Labour 0.8 (1.3) Political Party: Conservative 2.0 (1.3) Frequency of Dissent: sometimes −0.0 (1.9) Frequency of Dissent: rarely 2.6 (1.9) Frequency of Dissent: often −1.2 (1.7) Frequency of Dissent: never 3.3 (1.6) Constituency Effort: 4 4.0 (1.8) Constituency Effort: 3 −1.1 (1.8) Constituency Effort: 2 1.3 (1.7) Constituency Effort: 1 1.1 (1.8) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.11: Campbell, Cowley, Vivyan, and Wagner (2016), UK - Type of MP Dissent

Views important for policy: personal 2.1 (1.4) Views important for policy: constituents 0.7 (1.4) Type of Dissent: tends not to 4.5 (1.7) Type of Dissent: internal only −0.4 (1.6) Type of Dissent: internal and external 0.6 (1.6) Political Party: Labour 0.1 (1.4) Political Party: Conservative 2.9 (1.4) Constituency Effort: 4 0.9 (1.8) Constituency Effort: 3 0.5 (2.3) Constituency Effort: 2 1.6 (1.8) Constituency Effort: 1 2.9 (1.9) −20 −10 0 10 20 CATE estimate in percentage points

12 Figure A.12: Carnes and Lupu (2016), Argentina

Occupation: Factory Worker 3.7 (3.5) Occupation: Business Owner 1.5 (3.1) Ideology: Radical −0.0 (3.2) Ideology: Peronist 6.0 (3.3) Expereience: Three years experience 2.6 (3.2) Expereience: No Experience 3.1 (3.3) Education: Finished high school 0.9 (3.2) Education: Did not finish high school 4.3 (3.3) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.13: Carnes and Lupu (2016), UK

Party: Labour Party 1.4 (2.1) Party: Conservative Party 3.3 (2.1) Occupation: factory worker 2.2 (2.2) Occupation: business owner 2.5 (2.1) Education: left school at 16 3.6 (2.2) Education: graduated from university 1.1 (2.1) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.14: Carnes and Lupu (2016), USA

Race: White 7.5 (4.2) Race: Black −8.1 (4.4) Office: the state legislature 8.0 (6.7) Office: mayor 1.6 (6.7) Office: governor −4.5 (5.7) Office: city council −6.1 (6.7) Occupation: Factory worker −1.8 (4.5) Occupation: Business owner 1.1 (4.4) Education: Republican −4.5 (4.6) Education: Democrat 4.1 (4.4) −20 −10 0 10 20 CATE estimate in percentage points

13 Figure A.15: Clayton, Robinson, Johnson, Muriaas (2019), Malawi

Secondary Education: Secondary 4.4 (2.2) Secondary Education: Primary 6.8 (2.4) Occupation: Tobacco farmer 1.4 (2.8) Occupation: Teacher 11.9 (2.9) Occupation: Leadership experience 3.7 (2.8) Leadership experience: 1 3.2 (3.6) Leadership experience: 0 6.1 (1.8) Kinship Type: Patrilineal 5.1 (2.3) Kinship Type: Matrilineal 5.9 (2.4) Issue Priority: Priority: Roads 3.0 (3.1) Issue Priority: Priority: Education 9.3 (3.0) Issue Priority: Priority: Child marriage 5.4 (3.1) Issue Priority: Priority: Boreholes 4.2 (3.6) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.16: Clayton and Nyhan (2020), USA - Donors

Voting: Supports voter ID laws −0.5 (1.4) Voting: Opposes voter ID laws 3.5 (1.4) Taxes: More progressive 2.0 (1.4) Taxes: Less progressive 0.6 (1.4) Race: White 0.5 (1.3) Race: Hispanic 4.6 (2.2) Race: Black 0.2 (2.2) Partisanship: Republican 2.1 (1.4) Partisanship: Democrat 0.4 (1.4) Investigations: Partisan involvement 1.7 (1.4) Investigations: Independent 1.2 (1.3) Discrimination: Prevent discrimination 1.7 (1.4) Discrimination: Not a big problem 1.3 (1.4) Courts: Obey courts 2.3 (1.3) Courts: Disregard politicized decisions 0.3 (1.4) Compromise: Supports compromise 1.3 (1.3) Compromise: Stand up to other party 1.4 (1.4) −20 −10 0 10 20 CATE estimate in percentage points

14 Figure A.17: Clayton and Nyhan (2020), USA - YouGov

Voting: Supports voter ID laws −1.0 (1.1) Voting: Opposes voter ID laws 0.5 (1.1) Taxes: More progressive 0.0 (1.0) Taxes: Less progressive −0.5 (1.1) Race: White −0.1 (1.0) Race: Hispanic −0.7 (1.7) Race: Black −0.1 (1.6) Partisanship: Republican 0.9 (1.1) Partisanship: Democrat −1.3 (1.0) Investigations: Partisan involvement −0.5 (1.0) Investigations: Independent 0.1 (1.1) Discrimination: Prevent discrimination −0.3 (1.0) Discrimination: Not a big problem −0.1 (1.0) Courts: Obey courts −0.5 (1.1) Courts: Disregard politicized decisions −0.2 (1.0) Compromise: Supports compromise 1.0 (1.1) Compromise: Stand up to other party −1.3 (1.0) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.18: Costa (2020), USA - Lucid

Party: Republican Party: Democrat Latest Tweet: Republicans are CORRUPT and IMMORAL. I will not sit silent while they lie to Americans and steer us in the wrong direction. Latest Tweet: Providing Medicare for all Americans is NOT the right solution to fix health care in this country. Latest Tweet: One way to start fixing the immigration problem in this country is to increase spending for border security between the U.S. and Mexico. Latest Tweet: Increasing spending on border security between the U.S. and Mexico would NOT fix immigration policy in this country. Latest Tweet: Everyone in this country deserves basic health care. This is why we must support Medicare for all Americans. Latest Tweet: Democrats are CORRUPT and IMMORAL. I will not sit silent while they lie to Americans and steer us in the wrong direction. Constituent Relations: Answers over 90 percent of constituent mail Constituent Relations: Answers less than half of constituent mail

CATE estimate in percentage points

15 Figure A.19: Eggers, Vivyan, and Wagner (2018), UK

Seat Type: LabLib 4.5 (3.8) Seat Type: LabCon −5.6 (3.5) Seat Type: ConLib 12.2 (4.1) Seat Type: ConLab 2.9 (3.6) Occupation: Teacher 4.8 (4.2) Occupation: Political Advisor 3.8 (4.1) Occupation: Journalist 1.3 (4.1) Occupation: GP 4.0 (4.1) Occupation: Business Manager −1.0 (4.3) Conduct: Good Conduct 3.3 (2.4) Conduct: Bad Conduct 2.1 (2.7) Age: 64 5.7 (3.3) Age: 52 0.8 (3.2) Age: 45 1.6 (3.2) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.20: Goyal (2020), India

Policy: Water 4.7 (2.3) Policy: Vague 7.2 (2.3) Policy: Roads 3.9 (2.2) Policy: Health 6.6 (2.2) Policy: Education 4.0 (2.3) Party: None 6.3 (1.4) Party: INC 3.4 (2.4) Party: BJP 5.5 (2.6) Party: AAP 3.9 (2.5) Occupation: Teacher 7.0 (2.1) Occupation: Property Dealer 6.4 (2.1) Occupation: Lawyer 5.8 (2.0) Occupation: Farmer 2.4 (2.1) Caste: SC 4.7 (1.8) Caste: Muslim 6.6 (1.8) Caste: General 5.1 (1.8) Background: Onetime MLA 6.5 (1.7) Background: None 4.9 (1.8) Background: MPs Family/3rd gen 4.6 (1.8) −20 −10 0 10 20 CATE estimate in percentage points

16 Figure A.21: Hainmueller, Hopkins, and Yamamoto (2014), USA

Religion: None 2.4 (4.2) Religion: Mormon −5.3 (3.7) Religion: Mainline protestant −0.4 (4.4) Religion: Jewish 1.9 (4.6) Religion: Evangelical protestant −3.5 (3.9) Religion: Catholic 4.2 (4.3) Race: White 2.8 (4.2) Race: Native American −3.9 (4.3) Race: Hispanic −3.8 (4.3) Race: Caucasian 7.3 (4.3) Race: Black −2.6 (3.9) Race: Asian American −1.6 (3.9) Occupation: Lawyer −2.7 (4.2) Occupation: High school teacher −3.3 (4.3) Occupation: Farmer 7.5 (4.3) Occupation: Doctor 1.4 (4.3) Occupation: Car dealer 0.6 (3.7) Occupation: Business owner −4.4 (4.2) Miltary: Served −1.8 (2.6) Miltary: Did Not Serve 1.6 (2.5) Income: 92K 4.1 (4.4) Income: 65K 2.0 (3.9) Income: 54K −8.7 (4.6) Income: 5.1M −0.1 (4.1) Income: 32K 4.0 (4.0) Income: 210K −3.3 (4.3) Education: State university 0.5 (4.0) Education: Small college −5.1 (4.1) Education: No BA 4.7 (4.0) Education: Ivy League university 1.6 (3.9) Education: Community college −5.8 (4.4) Education: Baptist college 2.9 (4.4) Age: 75 2.3 (4.1) Age: 68 3.8 (4.3) Age: 60 0.8 (4.3) Age: 52 −1.1 (4.4) Age: 45 −3.4 (4.3) Age: 36 −3.9 (3.8) −20 −10 0 10 20 CATE estimate in percentage points

17 Figure A.22: Harris, Kao, and Lust (2020), Malawi

Type of future promise: Peronal Assistance 0.4 (1.6) Type of future promise: Health Care Serivce −0.5 (1.6) Target of distribution: Voters who support him/her 1.7 (2.2) Target of distribution: Voters regardless of support −3.7 (2.1) Target of distribution: Communities who support him/her 2.1 (2.2) Target of distribution: Communities regardless of support −0.4 (2.2) Partisanship: Non−Co−Party 0.6 (1.6) Partisanship: Co−Party −0.7 (1.5) Living Status: Village nearby −0.3 (1.6) Living Status: Village far away 0.2 (1.6) Ethnicity: Non−Coethnic 1.0 (1.6) Ethnicity: Coethnic −1.1 (1.5) Endorser Endowment: Wealthy 1.0 (1.6) Endorser Endowment: None −1.1 (1.6) Election Type: Parliamentary −0.8 (1.6) Election Type: Local Council 0.6 (1.6) Actions at campaign rallies: Only Campaigning −0.6 (1.9) Actions at campaign rallies: Campainging + Handing out T−shirts & Hats −1.0 (2.0) Actions at campaign rallies: Campaigning + Handing out Money 1.2 (1.9) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.23: Harris, Kao, and Lust (2020), Zambia

Type of future promise: Peronal Assistance −1.2 (1.7) Type of future promise: Health Care Serivce −1.6 (1.7) Target of distribution: Voters who support him/her −4.1 (2.4) Target of distribution: Voters regardless of support 1.5 (2.4) Target of distribution: Communities who support him/her 0.5 (2.4) Target of distribution: Communities regardless of support −3.0 (2.5) Partisanship: Non−Co−Party −1.1 (1.8) Partisanship: Co−Party −1.8 (1.7) Living Status: Village nearby −2.9 (1.7) Living Status: Village far away 0.2 (1.7) Ethnicity: Non−Coethnic −1.2 (1.7) Ethnicity: Coethnic −1.6 (1.7) Endorser Endowment: Wealthy −1.1 (1.7) Endorser Endowment: None −1.6 (1.7) Election Type: Parliamentary −1.1 (1.7) Election Type: Local Council −1.7 (1.7) Actions at campaign rallies: Only Campaigning −9.1 (2.1) Actions at campaign rallies: Campainging + Handing out T−shirts & Hats 2.4 (2.1) Actions at campaign rallies: Campaigning + Handing out Money 2.4 (2.1) −20 −10 0 10 20 CATE estimate in percentage points

18 Figure A.24: Henderson, John A., Logan Dancey, Stephen N. Goggin, Geoffrey Sheagley, and Alexander G. Theodoridis (2019), USA

Religion: Protestant 1.5 (1.3) Religion: None Listed 1.5 (1.5) Religion: Evangelical Protestant 0.7 (2.2) Religion: Catholic 2.3 (1.5) Race: White 2.1 (1.1) Race: Hispanic 1.7 (1.5) Race: Black −0.1 (1.5) Profession: Teacher −4.8 (2.5) Profession: State Legislator 4.7 (2.6) Profession: Small Business Owner −2.3 (2.6) Profession: Political Staffer 6.0 (2.6) Profession: Former US Army Major 3.6 (2.5) Profession: Farmer 4.0 (2.5) Profession: Factory Foreman −2.2 (2.4) Profession: City Council Member −0.4 (2.6) Profession: CEO 0.7 (2.5) Profession: Attorney 7.4 (2.6) Political Record: Work across the aisle to get things done 0.2 (1.8) Political Record: Stand with my party to do what's right 2.7 (1.8) Political Record: Secure appointment to a powerful legislative committee 1.3 (1.8) Political Record: Refuse to compromise my principles even when it means taking on my party 4.8 (1.8) Political Record: Help my constituents get the benefits they deserve −1.0 (1.8) Personality: Strong Leader −1.0 (2.2) Personality: Moral 4.3 (2.2) Personality: Knowledgeable −1.2 (2.3) Personality: Intelligent 3.6 (2.3) Personality: Inspiring 4.6 (2.2) Personality: Empathetic 3.1 (2.2) Personality: Decent −0.2 (2.3) Personality: Compassionate −0.3 (2.3) Issue Position 2: Toughen sentences and penalties for criminals 1.8 (3.7) Issue Position 2: Strengthen our military and national defense −10.7 (3.9) Issue Position 2: Strengthen gun control through commonsense restrictions −2.8 (3.4) Issue Position 2: Strengthen border security to stop illegal immigration 2.5 (3.9) Issue Position 2: Regulate CO2 emissions to combat global warming −4.8 (3.3) Issue Position 2: Reform policing and stop racial profiling 11.2 (3.1) Issue Position 2: Reduce the size of military and number of military bases 7.8 (3.1) Issue Position 2: Raise taxes on those making more than $250,000 a year 8.3 (3.2) Issue Position 2: Provide a path to citizenship for undocumented immigrants 0.9 (3.1) Issue Position 2: Protect the lives of the unborn −0.6 (4.2) Issue Position 2: Protect jobs and industry from unfair foreign trade 11.9 (3.3) Issue Position 2: Protect gun owners' rights to defend themselves and others 5.6 (4.4) Issue Position 2: Protect a woman's right to choose 5.2 (3.4) Issue Position 2: Promote expanding free trade agreements −3.2 (3.8) Issue Position 2: Prevent and prosecute abuse of government assistance programs −0.2 (3.9) Issue Position 2: Expand government and unemployment assistance for those in need −0.0 (3.1) Issue Position 2: Expand domestic oil and gas production through drilling −7.9 (3.7) Issue Position 2: Defend traditional marriage and religious beliefs −2.3 (4.7) Issue Position 2: Defend the rights of LGBT individuals 6.9 (3.3) Issue Position 2: Cut taxes on income and capital gains for all −11.4 (3.4) Issue Position 1: Toughen sentences and penalties for criminals −0.5 (3.8) Issue Position 1: Strengthen our military and national defense 1.6 (3.7) Issue Position 1: Strengthen gun control through commonsense restrictions 1.3 (3.5) Issue Position 1: Strengthen border security to stop illegal immigration −6.9 (3.8) Issue Position 1: Regulate CO2 emissions to combat global warming 4.4 (3.3) Issue Position 1: Reform policing and stop racial profiling −0.8 (3.3) Issue Position 1: Reduce the size of military and number of military bases 8.3 (3.1) Issue Position 1: Raise taxes on those making more than $250,000 a year 10.2 (3.3) Issue Position 1: Provide a path to citizenship for undocumented immigrants 4.7 (3.2) Issue Position 1: Protect the lives of the unborn −0.9 (4.3) Issue Position 1: Protect jobs and industry from unfair foreign trade 9.6 (3.2) Issue Position 1: Protect gun owners' rights to defend themselves and others −9.2 (4.2) Issue Position 1: Protect a woman's right to choose 4.4 (3.3) Issue Position 1: Promote expanding free trade agreements 0.5 (3.8) Issue Position 1: Prevent and prosecute abuse of government assistance programs −5.6 (4.0) Issue Position 1: Expand government and unemployment assistance for those in need 1.3 (3.2) Issue Position 1: Expand domestic oil and gas production through drilling 0.9 (3.9) Issue Position 1: Defend traditional marriage and religious beliefs −12.4 (4.1) Issue Position 1: Defend the rights of LGBT individuals 7.6 (3.5) Issue Position 1: Cut taxes on income and capital gains for all −8.4 (3.8) Endorsements: Veterans groups (American Legion, American Veterans) 4.7 (2.2) Endorsements: Tea Party groups (FreedomWorks, Tea Party Patriots) 1.3 (3.7) Endorsements: Tax reform groups (Club for Growth, Americans for Tax Reform) −9.8 (3.9) Endorsements: Reproductive rights groups (Planned Parenthood, NARAL) 11.9 (2.8) Endorsements: Major area newspapers (Tribune, Herald) −1.0 (2.2) Endorsements: Labor unions (AFL−CIO, SEIU) 0.3 (2.8) Endorsements: Gun rights groups (NRA, Gun Owners of America) 6.0 (3.6) Endorsements: Gun control groups (Coalition to Stop Gun Violence, Brady Campaign) 5.3 (3.1) Endorsements: Environmental groups (Sierra Club, Natural Resources Defense Council) 0.2 (2.9) Endorsements: Energy groups (American Petroleum and Mining Associations) −5.2 (3.5) Endorsements: Civil rights groups (key figures in the NAACP and Urban League) 3.0 (2.8) Endorsements: Christian groups (Family Research Council, Focus on the Family) −0.6 (3.8) Endorsements: Business groups (Chamber of Commerce, Small Business Associations) 0.3 (2.2) −20 −10 0 10 20 19CATE estimate in percentage points Figure A.25: Holman, Merolla, and Zechmeister (2016), USA

Opponent: Male Opponent 2.3 (5.3)

Opponent: Female Opponent 1.5 (5.5)

Context: Terror Threat −5.7 (5.5)

Context: Good Times 9.9 (5.4)

−20 −10 0 10 20 CATE estimate in percentage points

Figure A.26: Hopkins, Daniel (2014), USA

Religion: Protestant −3.4 (2.2) Religion: None Reported 0.0 (2.3) Religion: Evangelical Protestant −3.0 (2.3) Religion: Catholic 1.3 (2.4) Political Party: Republican −1.0 (1.8) Political Party: Independent −3.1 (2.6) Political Party: Democrat −0.7 (1.8) Issue Position 2: Restrict same−sex marriage −1.9 (2.8) Issue Position 2: Restrict gun access 1.6 (2.9) Issue Position 2: Restrict abortion access −4.4 (2.7) Issue Position 2: Protect gun ownership −2.0 (2.8) Issue Position 2: Protect abortion access 1.8 (2.8) Issue Position 2: Allow same−sex marriage −3.2 (2.8) Issue Position 1: Reduce taxes −3.0 (2.6) Issue Position 1: Reduce government spending 1.8 (2.8) Issue Position 1: Reduce global warming −1.3 (2.7) Issue Position 1: Reduce crime 1.0 (3.0) Issue Position 1: Improve schools −4.4 (2.9) Issue Position 1: Improve health care −1.8 (2.8) Annual income: $92,000 3.6 (2.9) Annual income: $65,000 −0.4 (2.7) Annual income: $54,000 −1.3 (2.9) Annual income: $5.1 million −2.8 (2.8) Annual income: $32,000 −1.1 (2.8) Annual income: $210,000 −5.6 (2.9) −20 −10 0 10 20 CATE estimate in percentage points

20 Figure A.27: Horne (2020), UK

Party: Labour 2.5 (0.9) Party: Conservative 1.9 (0.9) Occupation: RetailSalesperson 1.1 (1.3) Occupation: PoliticalAdvisor 2.8 (1.3) Occupation: Lawyer 3.2 (1.7) Occupation: FactoryWorker 0.1 (1.3) Occupation: Businessperson 4.2 (1.3) Ideology: Open Right 2.8 (1.1) Ideology: Open Left 3.3 (1.5) Ideology: Closed Right −0.7 (1.5) Ideology: Closed Left 2.7 (1.1) Education: University 4.2 (1.0) Education: Secondary 1.5 (1.2) Education: PostGrad 0.8 (1.0) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.28: Teele, Kalla, and Rosenbluth (2018), USA

Spouse's Job: Unmarried 3.7 (2.5) Spouse's Job: Farmer 3.1 (2.5) Spouse's Job: Doctor 7.9 (2.5) Occupation: Third grade teacher 2.3 (2.8) Occupation: State legislator 3.1 (2.8) Occupation: Mayor 8.3 (2.9) Occupation: Corporate lawyer 5.6 (2.8) Experience: None 3.2 (2.8) Experience: 8 7.4 (2.9) Experience: 3 2.3 (2.9) Experience: 1 6.2 (2.8) Children: 3 4.0 (2.5) Children: 1 4.1 (2.6) Children: 0 6.5 (2.4) Age: 65 5.0 (2.6) Age: 45 6.0 (2.5) Age: 29 3.9 (2.5) −20 −10 0 10 20 CATE estimate in percentage points

21 Figure A.29: Kirkland and Coppock (2017), USA - MTurk

Race: White 4.4 (1.9) Race: Hispanic 3.7 (1.9) Race: Black 4.2 (1.8) Race: Asian 3.9 (1.8) Party: White 4.4 (1.9) Party: Hispanic 3.7 (1.9) Party: Black 4.2 (1.8) Party: Asian 3.9 (1.8) Occupation: Small Business Owner 5.8 (2.0) Occupation: Police Officer 3.5 (2.0) Occupation: Educator 2.1 (2.0) Occupation: Business Executive 3.5 (2.0) Occupation: Attorney 5.2 (2.1) Experience: State Legislator −0.4 (2.1) Experience: Representative in Congress 3.2 (2.0) Experience: None 5.7 (1.9) Experience: Mayor 5.3 (1.9) Experience: City Council Member 6.6 (2.1) Age: 65 3.4 (1.8) Age: 55 2.2 (1.9) Age: 45 4.6 (1.9) Age: 35 5.7 (1.8) −20 −10 0 10 20 CATE estimate in percentage points

22 Figure A.30: Kirkland and Coppock (2017), USA - YouGov

Race: White 6.5 (2.9) Race: Hispanic 6.9 (2.6) Race: Black 1.1 (2.7) Race: Asian 1.8 (3.2) Party: White 6.5 (2.9) Party: Hispanic 6.9 (2.6) Party: Black 1.1 (2.7) Party: Asian 1.8 (3.2) Occupation: Stay−at−Home Dad/Mom 1.0 (3.8) Occupation: Small Business Owner −0.2 (4.1) Occupation: Police Officer −0.1 (3.6) Occupation: Electrician 4.8 (3.5) Occupation: Educator 5.8 (3.8) Occupation: Business Executive 5.2 (3.8) Occupation: Attorney 11.4 (3.5) Experience: State Legislator 6.6 (3.3) Experience: School Board President 7.1 (3.6) Experience: Representative in Congress 3.4 (3.5) Experience: None 1.8 (3.2) Experience: Mayor 0.7 (3.3) Experience: City Council Member 5.1 (3.0) Age: 65 0.1 (2.7) Age: 55 8.1 (2.6) Age: 45 2.3 (3.0) Age: 35 6.1 (2.8) −20 −10 0 10 20 CATE estimate in percentage points

23 Figure A.31: Leeper and Robison (2020), US, SSI

Trans−Pacific Partnership: Strongly support 0.4 (3.3) Trans−Pacific Partnership: Strongly oppose −0.7 (3.1) Trans−Pacific Partnership: Slightly support 1.6 (3.3) Trans−Pacific Partnership: Slightly oppose −0.3 (3.1) Trans−Pacific Partnership: Neither Support Nor Oppose 1.2 (3.0) Trans−Pacific Partnership: Moderately support 0.3 (3.1) Trans−Pacific Partnership: Moderately oppose 0.6 (3.1) Tax the rich: Strongly support −1.9 (3.4) Tax the rich: Strongly oppose 3.2 (3.3) Tax the rich: Slightly support −2.7 (3.2) Tax the rich: Slightly oppose −3.2 (3.2) Tax the rich: Neither Support Nor Oppose 5.8 (3.2) Tax the rich: Moderately support 1.2 (3.1) Tax the rich: Moderately oppose −0.4 (3.2) Religion: None 3.4 (2.7) Religion: Muslim 3.4 (3.6) Religion: Mainline protestant −0.2 (2.7) Religion: Jewish 1.6 (4.0) Religion: Evangelical protestant −0.2 (2.7) Religion: Catholic −2.7 (2.7) Race: White 1.9 (1.5) Race: Hispanic −1.5 (3.1) Race: Asian American −1.5 (4.0) Race: African American −2.3 (3.0) Path to citizenship: Strongly support 1.1 (3.1) Path to citizenship: Strongly oppose 1.2 (3.2) Path to citizenship: Slightly support 2.1 (3.3) Path to citizenship: Slightly oppose 0.5 (3.1) Path to citizenship: Neither Support Nor Oppose −1.6 (3.2) Path to citizenship: Moderately support 4.8 (3.2) Path to citizenship: Moderately oppose −4.9 (3.2) Party: Republican −0.2 (1.7) Party: Democrat 1.1 (1.6) Occupation: U.S. Senator 2.2 (2.3) Occupation: State Governor −2.1 (2.5) Occupation: Member of Congress 4.2 (2.3) Occupation: CEO −2.6 (2.4) Military Service: Served −0.4 (1.7) Military Service: Did not serve 1.4 (1.7) ISIS: Strongly support 1.5 (3.0) ISIS: Strongly oppose −2.4 (3.2) ISIS: Slightly support 7.0 (3.2) ISIS: Slightly oppose −0.0 (3.1) ISIS: Neither Support Nor Oppose 2.0 (3.1) ISIS: Moderately support 1.4 (3.1) ISIS: Moderately oppose −6.4 (3.3) Education: State university −0.0 (2.4) Education: Small college 0.9 (2.4) Education: Ivy League university −0.4 (2.3) Education: Community college 1.3 (2.3) Cap and trade: Strongly support 0.0 (3.2) Cap and trade: Strongly oppose −2.2 (3.3) Cap and trade: Slightly support 0.8 (3.1) 0.8 (3.1) Cap and trade: Slightly oppose 24 Cap and trade: Neither Support Nor Oppose −3.1 (3.2) Cap and trade: Moderately support 2.2 (3.3) Cap and trade: Moderately oppose 5.4 (3.1) −20 −10 0 10 20 CATE estimate in percentage points Figure A.32: Lemi (2020), USA, Qualtrics

Party: Republican 5.3 (2.3) Party: Independent 3.8 (2.1) Party: Democrat 0.6 (2.1) Nativity: Born Outside the U.S. 2.9 (1.7) Nativity: Born in the U.S. 4.0 (1.8) Ideology: Moderate 2.1 (2.2) Ideology: Liberal 1.2 (2.1) Ideology: Conservative 6.6 (2.1) Experience: Served in the State Legislature 6.6 (2.1) Experience: Served in Congress 3.2 (2.2) Experience: Served in City Council 0.8 (2.1) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.33: Mares and Visconti (2020), Romania

Positive Inducement: Social assistance −3.0 (3.3) Positive Inducement: No money offer 2.9 (3.0) Positive Inducement: 100 RON −3.0 (3.3) Policy/Public Goods: Renovate schools and roads −0.5 (3.3) Policy/Public Goods: Renovate schools −0.9 (3.2) Policy/Public Goods: No promises −1.6 (3.2) Negative Inducement: Threat to non−supporters −0.2 (2.5) Negative Inducement: No threat −1.9 (2.7) Investigation: Sentenced 0.5 (3.3) Investigation: Investigated −3.6 (3.2) Investigation: Clean 0.6 (2.9) Income: No high income −1.6 (2.6) Income: High income −0.5 (2.4) Experience: Incumbent −0.4 (2.5) Experience: Challenger −1.7 (2.8) −20 −10 0 10 20 CATE estimate in percentage points

25 Figure A.34: Martin and Blinder (2020), UK, YouGov

Party: Labour −0.4 (1.6) Party: Conservatives −1.1 (1.6) Law enforcement: Race equality laws −2.1 (1.6) Law enforcement: Anti−social behaviour 1.0 (1.6) Immigration policy: Strictly limited 1.5 (1.9) Immigration policy: Skilled immigration −1.3 (1.9) Immigration policy: Refugees −2.2 (1.9) Ethnicity: white British −1.0 (1.9) Ethnicity: Pakistani 3.6 (1.9) Ethnicity: black Caribbean −4.7 (2.0) Entry into politics: List of underrepresented candidates −1.0 (1.6) Entry into politics: Getting involved −0.3 (1.6) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.35: Mo (2015), Florida

Competition: malestrong −52.8 (3.3)

Competition: femalestrong 58.7 (3.0)

Competition: demodist 2.7 (5.0)

Competition: bothstrong 12.1 (3.5)

−50 0 50 CATE estimate in percentage points

26 Figure A.36: Ono and Yamada (2018), Japan

Specialization: Social Welfare −4.1 (1.7) Specialization: National Defense −1.8 (1.7) Specialization: Foreign Affairs −3.7 (1.6) Specialization: Environmental Issues 1.5 (1.6) Specialization: Economic Policy −5.6 (1.7) Specialization: Consumer Issues −3.3 (1.7) Social Issues: Liberal −3.5 (1.0) Social Issues: Conservative −2.3 (1.0) Military Issues: Liberal −3.0 (1.0) Military Issues: Conservative −2.6 (1.0) Education: University degree −0.6 (1.2) Education: High school degree −4.1 (1.2) Education: Graduate degree −4.1 (1.2) Economic Issues: Liberal −3.0 (1.0) Economic Issues: Conservative −2.8 (1.0) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.37: Saha and Weeks (2019)

Progressive: 1 5.2 (2.4) Progressive: 0 7.0 (2.5) Political Experience: More than 20 7.4 (3.6) Political Experience: 5 − 10 7.8 (3.7) Political Experience: 10 − 20 2.0 (3.5) Political Experience: 0 − 5 7.7 (3.5) Political Agenda: Very Few Changes 5.7 (3.0) Political Agenda: Moderate Changes 8.1 (3.0) Political Agenda: Complete Overhaul 5.7 (3.0) −20 −10 0 10 20 CATE estimate in percentage points

27 Figure A.38: Saha and Weeks (2019)

Progressive: 1 9.0 (1.9) Progressive: 0 6.7 (2.0) Profession: Small business owner 12.2 (2.4) Profession: Educator 5.1 (2.4) Profession: Attorney 6.2 (2.4) Political Experience: 5 − 10 9.0 (2.0) Political Experience: 10 − 20 7.3 (2.9) Political Experience: 0 − 5 5.8 (2.7) Political Agenda: Very Few Changes 7.8 (2.2) Political Agenda: Moderate Changes 4.8 (2.6) Political Agenda: Complete Overhaul 10.3 (2.4) Age: 65 10.1 (2.9) Age: 55 5.8 (3.0) Age: 45 9.0 (2.9) Age: 35 6.6 (2.9) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.39: Saha and Weeks (2019)

Progressive: 1 2.5 (1.7) Progressive: 0 1.0 (1.6) Political Agenda: Very Few Changes 0.8 (2.0) Political Agenda: Moderate Changes 4.1 (2.0) Political Agenda: Complete Overhaul 1.4 (2.0) Personality traits: Tough Negotiator 1.3 (2.9) Personality traits: Hard−Working −0.8 (3.1) Personality traits: Good Communicator −0.3 (3.1) Personality traits: Empathetic 2.4 (2.9) Personality traits: Determined to Succeed 5.6 (3.0) Personality traits: Collaborative 3.5 (3.0) Personality traits: Assertive 1.5 (3.2) Family: No children 0.9 (2.3) Family: 3 children 4.4 (2.4) Family: 2 children 1.7 (2.4) Family: 1 child 0.3 (2.3) −20 −10 0 10 20 CATE estimate in percentage points

28 Figure A.40: Saha and Weeks (2019)

Progressive: 1 2.9 (1.5) Progressive: 0 3.6 (1.6) Political Agenda: Very Few Changes 4.1 (1.8) Political Agenda: Moderate Changes 0.8 (1.8) Political Agenda: Complete Overhaul 3.8 (1.9) Personality traits: Tough Negotiator 4.7 (2.9) Personality traits: Hard−Working 0.3 (2.9) Personality traits: Good Communicator 4.6 (2.8) Personality traits: Empathetic 1.5 (2.8) Personality traits: Determined to Succeed 1.8 (2.8) Personality traits: Collaborative 2.6 (2.9) Personality traits: Assertive 7.2 (2.7) Family: 3 4.5 (2.2) Family: 2 5.4 (2.2) Family: 1 3.2 (2.2) Family: 0 0.7 (2.1) −20 −10 0 10 20 CATE estimate in percentage points

29 Figure A.41: Sen, Maya (2017), USA

Religion: Mormon 1.0 (3.2) Religion: Mainline Protestant 8.5 (3.3) Religion: Jewish 3.1 (3.3) Religion: Evangelical Protestant 1.7 (3.3) Religion: Catholic 6.8 (3.1) Race/Ethnicity: White 8.0 (2.8) Race/Ethnicity: Nonwhite 3.0 (1.7) Profession: State judge 3.1 (4.2) Profession: Public defender 3.9 (4.1) Profession: Prosecutor −0.0 (4.0) Profession: Non−profit lawyer 5.8 (4.0) Profession: Lower−level federal judge 5.3 (4.0) Profession: Lawyer in private practice 7.5 (4.0) Profession: Law professor 2.4 (4.3) Profession: Elected politician 5.8 (3.7) Political Party: Strong Republican −0.2 (3.1) Political Party: Strong Democrat 7.0 (3.1) Political Party: Leans Republican 8.4 (3.1) Political Party: Leans Democrat 4.3 (3.2) Political Party: Independent 2.0 (3.3) Education: Law School Ranked in Top 14 5.9 (3.2) Education: Law School Ranked #50−100 2.4 (3.1) Education: Law School Ranked #25−50 9.5 (3.2) Education: Law School Ranked #15−25 0.3 (3.3) Education: Law School Not Ranked in Top 100 1.8 (3.0) Court experience: Served as a law clerk 6.4 (2.1) Court experience: Did not serve as a law clerk 2.4 (2.0) Age: Aged over 70 years 4.5 (3.0) Age: Aged between 60 and 70 years 6.8 (3.1) Age: Aged between 50 and 60 years 4.6 (3.2) Age: Aged between 40 and 50 years 0.5 (3.3) Age: Aged between 30 and 40 years 5.7 (3.3) −20 −10 0 10 20 CATE estimate in percentage points

30 Figure A.42: Sen, Maya (2017), USA

Religion: Mormon 4.8 (3.1) Religion: Mainline Protestant 1.7 (3.1) Religion: Jewish 2.7 (3.3) Religion: Evangelical Protestant 1.1 (3.4) Religion: Catholic 5.3 (3.0) Race/Ethnicity: White 5.2 (2.9) Race/Ethnicity: Nonwhite 2.4 (1.7) Profession: State judge 6.1 (4.2) Profession: Public defender 1.8 (4.2) Profession: Prosecutor 1.9 (3.9) Profession: Non−profit lawyer −2.9 (4.4) Profession: Lower−level federal judge 6.6 (4.1) Profession: Lawyer in private practice 3.2 (4.4) Profession: Law professor 7.7 (4.1) Profession: Elected politician 2.1 (3.9) Education: Law School Ranked in Top 14 −2.8 (3.3) Education: Law School Ranked #50−100 4.0 (3.2) Education: Law School Ranked #25−50 2.8 (3.2) Education: Law School Ranked #15−25 6.1 (3.4) Education: Law School Not Ranked in Top 100 6.4 (2.9) Court experience: Served as a law clerk 3.7 (2.1) Court experience: Did not serve as a law clerk 3.1 (2.0) Age: Aged over 70 years −3.2 (3.1) Age: Aged between 60 and 70 years 8.8 (3.2) Age: Aged between 50 and 60 years 1.8 (3.3) Age: Aged between 40 and 50 years 3.3 (3.3) Age: Aged between 30 and 40 years 4.9 (3.3) −20 −10 0 10 20 CATE estimate in percentage points

31 Figure A.43: Shaffner and Green (2020), YouGov Blue

Strategy: Persuade moderates 4.1 (0.8) Strategy: Energize base 3.8 (0.9) Health: Public option 2.4 (1.1) Health: Medicare for all 6.3 (1.0) Health: ACA expansion 3.3 (1.0) Environment: Net zero by 2050 2.2 (1.0) Environment: Net zero by 2045 4.4 (1.0) Environment: Net zero by 2030 5.3 (1.0) Background: Outsider 3.6 (0.8) Background: Establishment 4.4 (0.8) Age: Age 75 3.7 (1.7) Age: Age 70 4.0 (1.8) Age: Age 65 7.2 (1.8) Age: Age 60 7.1 (1.7) Age: Age 55 5.3 (1.7) Age: Age 50 2.5 (1.7) Age: Age 45 1.5 (1.8) Age: Age 40 2.7 (1.7) Age: Age 35 2.1 (1.8) −20 −10 0 10 20 CATE estimate in percentage points

Figure A.44: Simas and Murdoch (2019), USA, Mturk

2.5 (4.0) Party: Republican

3.6 (4.0) Party: Democrat

−20 −10 0 10 20 CATE estimate in percentage points

32 Figure A.45: Visconti (2018), Chile

Policy: NO entregar ayuda economica 0.1 (2.2) Policy: Entregar ayuda economica 1.9 (2.4) Occupation: Profesor(a) −4.0 (2.9) Occupation: Jardinero(a) 2.7 (3.3) Occupation: Ingeniero(a) 4.2 (3.0) Ideology: Izquierda 4.0 (3.4) Ideology: Independiente 2.4 (3.5) Ideology: Derecha −1.5 (3.6) Ideology: Centro −0.9 (3.2) Experience: Sin experiencia 1.4 (2.8) Experience: Concejal 5.9 (3.0) Experience: Alcalde −4.5 (3.1) Age: 50 2.7 (2.9) Age: 40 2.4 (3.3) Age: 30 −2.0 (3.0) −20 −10 0 10 20 CATE estimate in percentage points

33 B Digital measurement of coefficient estimates

Figure 1 in the main text includes estimates from nine experiments in seven papers that we were only able to obtain by digitally measuring the coefficient plots included in the published papers. In this appendix, we provide evidence that our digital measurement technique produces accurate estimates. We used the “rectangular selection” tool in MacOS’s Preview application to measure the location of coefficient estimates (and 95% confidence intervals) in pixel units (see Figure B.46). We then converted pixels into the appropriate scale.

Figure B.46: Using the rectangular selection tool

To demonstrate that this procedure produces accurate estimates, we conducted a valida- tion exercise in which we digitally measured the coefficient estimates using a study for which we had the replication dataset. Figure B.47 shows that the digitally measured coefficients from Kirkland and Coppock (2018, Figure 3) match their directly estimated counterparts quite well. That said, the precision of the method is limited by the width of the pixel,

34 resulting in a small amount of measurement error. The average absolute error is 0.000747, or 0.075 percentage points. The correlation of the two sets of estimates is 0.9999726.

Figure B.47: Correlation of digital measurements with direct estimates

●

●

● 0.2 ●

●● ● ●

●●

● ●●● ● ● ●●● ●● ●● ●● 0.0 ●●● ●●● ●●● ●● ●● ●

● −0.2 Coefficient Estimate and 95% CI (Digitally measured)

−0.2 0.0 0.2 Coefficient Estimate and 95% CI (Estimated directly)

35 References

Aguilar, Rosario, Saul Cunow and Scott Desposato. 2015. “Choice Sets, Gender, and Can- didate Choice in Brazil.” Electoral Studies 39(Supplement C):230 – 242.

Armendariz, Karen Caballero, Ben Farrer and Monica Martinez. 2018. “Badge of Courage or Sign of Criminality? Experimental Evidence For How Voters Respond to Candidates With A Political Arrest In Their Past.” Paper provided in Appendix.

Arnesen, Sveinung, Dominik Duell and Mikael Poul Johannesson. 2019. “Do citizens make inferences from political candidate characteristics when aiming for substantive represen- tation?” Electoral Studies 57:46 – 60.

Atkeson, Lonna Rae and Brian T. Hamel. 2018. “Fit for the Job: Candidate Qualifications and Vote Choice in Low Information Elections.” Political Behavior; New York pp. 1–24.

Bansak, Kirk, Jens Hainmueller, Daniel J. Hopkins and Teppei Yamamoto. 2018. “Be- yond the Breaking Point? Survey Satisficing in Conjoint Experiments.” Political Analysis 26:112–119.

Bermeo, Nancy and Jasmine Bhatia. 2017. Strongmen or Technocrats? Experimental Evidence Testing Leadership Preferences in Afghanistan. Technical report International Growth Center.

Bischof, Daniel and Roman Senninger. 2020. “Do Voters Want Domestic Politicians to Scrutinize the European Union?” Unpublished Manuscript . URL: https://www.dropbox.com/s/9fp401dq2squojl/manuscript.pdf?dl=0

Blackman, Alexandra Domike and Marlette Jackson. 2019. “Gender Stereotypes, Political Leadership, and Voting Behavior in Tunisia.” Political Behavior .

Campbell, Rosie, Philip Cowley, Nick Vivyan and Markus Wagner. 2016. “Legislator Dissent as a Valence Signal.” British Journal of Political Science pp. 1–24.

Carnes, Nicholas and Noam Lupu. 2016. “Do Voters Dislike Working-Class Candidates? Voter Biases and the Descriptive Underrepresentation of the Working Class.” American Political Science Review 110(4):832–844.

Clayton, Amanda, Amanda Lea Robinson, Martha C Johnson and Ragnhild Muriaas. 2019. “(How) Do Voters Discriminate Against Women Candidates? Experimental and Qualita- tive Evidence From Malawi.” Comparative Political Studies 53(3-4):601–630.

Clayton, Katherine and Brendan Nyhan. 2020. “Who Will Defend Democracy? Evaluating Tradeoffs in Candidate Support Among Partisan Donors and Voters.” Unpublished Manuscript .

36 URL: https://preprints.apsanet.org/engage/api-gateway/apsa/assets/orp/resource/item/5d02becd39ef0400184a49fd/original/who- will-defend-democracy-evaluating-tradeoffs-in-candidate-support-among-partisan-donors- and-voters.pdf

Costa, Mia. 2020. “Ideology, Not Affect: What Americans Want From Political Representa- tion.” Unpublished Manuscript . Paper included in Appendix.

Crowder-Meyer, Melody, Shana Kushner Gadarian, Jessica Trounstine and Kau Vue. 2015. “Complex Interactions: Candidate Race, Sex, Electoral Institutions and Voter Choice.” Unpublished Manuscript . URL: https://bit.ly/3e2YB6p

Dahl, Malte and Jacob Nyrup. 2020. “Confident and cautious candidates: Explaining under- representation of women in Danish municipal politics.” European Journal of Political Re- search .

Doherty, David, Conor M. Dowling and Michael G. Miller. 2020. Small Power: How Local Parties Shape Elections. Unpublished book manuscript.

Eggers, Andrew C., Nick Vivyan and Markus Wagner. 2018. “Corruption, Accountability, and Gender: Do Female Politicians Face Higher Standards in Public Life?” The Journal of Politics 80(1):321–326.

Fox, Richard L. and Eric R. A. N. Smith. 1998. “The Role of Candidate Sex in Voter Decision-Making.” Political Psychology 19(2):405–419.

Goyal, Tanushree. 2020. “Local female representation as a pathway to power: A natural experiment in India.” Unpublished Manuscript . URL: https://papers.ssrn.com/sol3/papers.cfm?abstract id=3590118

Hainmueller, Jens, Daniel J. Hopkins and Teppei Yamamoto. 2014. “Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Ex- periments.” Political Analysis 22(1):1–30.

Harris, Adam, Kristen Kao and Ellen Lust. 2020. “Research Design for ’Levels Experiment’.” Unpublished Manuscript . Paper included in Appendix.

Henderson, John A., Logan Dancey, Stephen N. Goggin, Geoffrey Sheagley and Alexan- der G. Theodoridis. 2019. “Issues or Affinity? How Voters Decide in Primary Elections.” Unpublished manuscript . URL: https://bit.ly/2PD1voE

Hobolt, Sara B. and Toni Rodon. 2020. “Cross-cutting issues and electoral choice. EU issue voting in the aftermath of the Brexit referendum.” Journal of European Public Policy 27(2):227–245.

37 Holman, Mirya R., Jennifer L. Merolla and Elizabeth J. Zechmeister. 2016. “Terrorist Threat, Male Stereotypes, and Candidate Evaluations.” Political Research Quarterly 69(1):134– 147.

Hopkins, Daniel J. 2014. “Do Voting Criteria Differ across Levels of the U.S. Federal System? A Conjoint Experiment to Understand Voter Decision-making.”. URL: https://tessexperiments.org/data/hopkins365.html

Horiuchi, Yusaku, Daniel M. Smith and Teppei Yamamoto. 2020. “Identifying Voter Pref- erences for Politicians’ Personal Attributes: A Conjoint Experiment in Japan.” Political Science Research and Methods 8(1):75–91.

Horne, Will. 2020. “Do voters really want working class candidates?” Unpublished Manuscript . Paper included in Appendix.

Kage, Rieko, Frances Rosenbluth and Seiki Tanaka. 2018. “What Explains Low Female Political Representation? Evidence from Survey Experiments in Japan.” Politics and Gender 15(2).

Kang, Woo Chang, Jill Sheppard, Feodor Snagovsky and Nicholas Biddle. 2018. “Ethnic Identities and Descriptive Representation: A Conjoint Analysis of Vote Choice.” Unpub- lished manuscript . Paper provided in Appendix.

Kao, Kristen and Lindsay J. Benstead. 2021. “Female Electability in the Arab World: The Advantages of Intersectionality.” Comparative Politics .

Kirkland, Patricia A. and Alexander Coppock. 2018. “Candidate Choice Without Party Labels: New Insights from Conjoint Survey Experiments.” Political Behavior 40(3):571– 591.

Leeper, Thomas J. and Joshua Robison. 2020. “More Important, but for What Exactly? The Insignificant Role of Subjective Issue Importance in Vote Decisions.” Political Behavior 42(1):239–259.

Lemi, Danielle Casarez. 2020. “Do Voters Prefer Just Any Descriptive Representative? The Case of Multiracial Candidates.”.” Perspectives on Politics . Forthcoming.

Martin, Nicole S. and Scott Blinder. 2020. “Biases at the Ballot Box: How Multiple Forms of Voter Discrimination Impede the Descriptive and Substantive Representation of Ethnic Minority Groups.” Political Behavior . Forthcoming.

Mo, Cecilia Hyunjung. 2015. “The Consequences of Explicit and Implicit Gender Attitudes and Candidate Quality in the Calculations of Voters.” Political Behavior 37(2):357–395.

Ono, Yoshikuni and Barry C. Burden. 2018. “The Contingent Effects of Candidate Sex on Voter Choice.” Political Behavior; New York pp. 1–25. Forthcoming.

38 Ono, Yoshikuni and Masahiro Yamada. 2018. “Do voters prefer gender stereotypic candi- dates? evidence from a conjoint survey experiment in Japan.” Political Science Research and Methods pp. 1–16. Forthcoming.

Piliavin, Jane Allyn. 1987. “Age, Race, and Sex Similarity to Candidates and Voting Pref- erence1.” Journal of Applied Social Psychology 17(4):351–368.

Saha, Sparsha and Ana Catalano Weeks. 2019. “Ambitious Women: Gender and Voter Per- ceptions of Candidate Ambition.” Unpublished Manuscript . Paper provided in Appendix.

Schuler, Paul. 2020. “Gender Bias and Position Salience: A Theory and Test of Variable Political Gender Bias in a Single-Party Regime.” Unpublished Manuscript . Paper provided in Appendix.

Sen, Maya. 2017. “How Political Signals Affect Public Support for Judicial Nominations: Evidence from a Conjoint Experiment.” Political Research Quarterly 70:374–393.

Shaffner, Brian and Jon Green. 2020. “What attributes do Democratic primary voters value?”. URL: https://www.dataforprogress.org/blog/2019/7/11/what-attributes-do-democratic- primary-voters-value

Sigelman, Lee and Carol Sigelman. 1982. “Sexism, Racism, and Ageism in Voting Behavior: An Experimental Analysis.” Social Psychology Quarterly 45:263.

Simas, Elizabeth N. and Doug Murdoch. 2019. ““I Didn’t Lie, I Misspoke”: Voters’ Re- sponses to Questionable Campaign Claims.” Journal of Experimental Political Science pp. 1–14. Forthcoming.

Teele, Dawn Langan, Joshua Kalla and Frances Rosenbluth. 2018. “The Ties That Double Bind: Social Roles and Women’s Underrepresentation in Politics.” American Political Science Review 112(3):525–541.

Tomz, Michael and Robert P. Van Houweling. 2016. “Political Repositioning: A Conjoint Analysis.”. URL: https://web.stanford.edu/ tomz/working/Tomz-VH-Repositioning-Conjoint-2016- 04.pdf

Visconti, Giancarlo. 2017. “After the Flood: Natural Disasters and Political Preferences in Chile.” Paper included in Appendix.

Vivyan, Nick and Markus Wagner. 2015. “What Do Voters Want From Their Local MP?” The Political Quarterly 86(1):33–40.

Wuest, Reto and Jonas Pontusson. 2017. “Do Citizens Prefer Affluent Representatives? Evidence from a Survey Experiment in Switzerland.”. URL: https://www.ssrn.com/abstract=3077598

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